Zheng Yang – författare

Written in a cookbook style, this book offers solutions using a recipe based approach. Each recipe contains step-by-step instructions followed by an analysis of what was done in each task and other useful information. The cookbook approach means you can dive into whatever recipes you want in no particular order. If you are an aspiring programmer with some basic concepts in C# and object-oriented knowledge who wants to create games for Windows Phone 7, this book is for you. This book is also for the experienced programmers want to transfer from Windows or Xbox to the Windows Phone 7 platform. Only basic knowledge of C# and .Net is required.

Specifically focusing on WiFi fingerprint based localization via crowdsourcing, the book follows a top-down approach and explores the three most important aspects of wireless indoor localization: deployment, maintenance, and service accuracy. After extensively reviewing the state-of-the-art literature, it highlights the latest advances in crowdsourcing-enabled WiFi localization. It elaborated the ideas, methods and systems for implementing the crowdsourcing approach for fingerprint-based localization. By tackling the problems such as: deployment costs of fingerprint database construction, maintenance overhead of fingerprint database updating, floor plan generation, and location errors, the book offers a valuable reference guide for technicians and practitioners in the field of location-based services. As the first of its kind, introducing readers to WiFi-based localization from a crowdsourcing perspective, it will greatly benefit and appeal to scientists and researchers in mobile and ubiquitous computing and related areas. 

Perception of human beings has evolved from natural biosensor to powerful sensors and sensor networks. In sensor networks, trillions of devices are interconnected and sense a broad spectrum of contexts for human beings, laying the foundation of Internet of Things (IoT). However, sensor technologies have several limitations relating to deployment cost and usability, which render them unacceptable for practical use. Consequently, the pursuit of convenience in human perception necessitates a wireless, sensorless and contactless sensing paradigm.

Recent decades have witnessed rapid developments in wireless sensing technologies, in which sensors detect wireless signals (such as acoustic, light, and radio frequency) originally designed for data transmission or lighting. By analyzing the signal measurements on the receiver end, channel characteristics can be obtained to convey the sensing results. Currently, significant effort is being devoted to employing the ambient Wi-Fi, RFID, Bluetooth, ZigBee, and television signals for smart wireless sensing, eliminating the need for dedicated sensors and promoting the prospect of the Artificial Intelligence of Things (AIoT).

This book provides a comprehensive and in-depth discussion of wireless sensing technologies. Specifically, with a particular focus on Wi-Fi-based sensing for understanding human behavior, it adopts a top-down approach to introduce three key topics: human detection, localization, and activity recognition. Presenting the latest advances in smart wireless sensing based on an extensive review of state-of-the-art research, it promotes the further development of this area and also contributes to interdisciplinary research.

Time flies since the debut of this book. In the past ten years, localization technology has evolved from small saplings into towering trees. Robots and drones with autonomous positioning and navigation capabilities, once considered unreachable fantasies, have gradually become a reality. However, while we are being amazed at the groundbreaking changes brought about by technology, as researchers, we still need to remain acutely attentive to the current limitations of localization. Some significant challenges still impede the widespread deployment. For example, traditional Wi-Fi fingerprint-based wireless localization, due to various challenges in fingerprint database collection and maintenance, has remained stay in the laboratory, and even when using smartphones for localization in malls, we still cannot achieve the outdoor GPS-like experience. The list goes on and on.

Against this backdrop, the reissue of this book aims to more comprehensively reflect the latest developments in localization technology. We have added introductions to emerging technologies such as passive high-precision localization based on wireless signal CSl and autonomous localization for smart devices. Additionally, we have integrated and further streamlined technical chapters that now appear outdated adapting to the pace of the times.

This book aims to provide a comprehensive and in-depth view of location-awareness technology in today’s popular wireless networks. However, the obvious diversity of networks, from short-range Bluetooth to long-range telecommunication networks, makes it very challenging to organize materials. Although general principles exist, the implementation differs from network to network and application to application.

The book can serve as a guidebook for the technicians and practitioners in the industry of location systems. They can expect to obtain a comprehensive understanding of the field, in order to compare and select localization solutions fulfilling various application requirements. Abundant references in the book open up a broader domain for advanced study. In addition, the book is tailored toward a textbook for college researchers and graduate students.

In an age where real-time processing and interaction with the physical world through digital lenses are paramount, visual SLAM technology has become the backbone of mobile AR/VR applications, robotics, and autonomous systems. However, the demanding computational load of visual SLAM often strains the limited resources of mobile devices, hindering performance and accuracy. This is exactly where edge computing comes to the forefront, offering a potent solution by performing data processing at the edge of the network, closer to the source of data.

This monograph is a pioneering exploration into how edge computing can elevate visual SLAM systems, overcoming the traditional challenges of computational intensity and resource constraints. Edge computing not only offloads heavy-duty processing from mobile devices to edge servers but also mitigates latency, enhances efficiency, and ensures robust, real-time performance. This monograph unveils the transformative potential of edge-assisted visual SLAM, presenting groundbreaking research and the latest advancements in task decoupling, collaborative mapping, and environmental interaction.

This monograph could serve as a scholarly resource for those within the fields of computer vision and mobile computing. It presents a detailed exploration of current research in edge-assisted visual SLAM and anticipates future developments, offering readers a comprehensive understanding of the field''s trajectory and its implications for the next generation of mobile applications and autonomous systems.